Optimization in Machine Learning and Data Science

Machine learning (ML) and artificial intelligence (AI) have burst into public consciousness in the last several years. While large language and multimodal models like GPT-4 have recently taken the excitement to a new level, developments in voice recognition software, novel recommendation systems for online retailers and streaming services, superhuman-level play by computers in Chess and Go, and unfulfilled promises in technologies like self-driving cars have been generating interest for more than a decade. Many research disciplines are feeling the profound effects of AI. For example, scientists can now utilize neural networks (NNs) to predict a protein's structure based on its amino acid sequence [3] -- a problem that was identified decades ago as a grand challenge for computational science. ML, AI, data science, data analysis, data mining, and statistical inference all have different but overlapping meanings; the term "data science" is perhaps the most general.